Apparatus and methods for converting raster illustrated parts images into intelligent vector-layered files

ABSTRACT

Apparatus and methods for converting raster illustrated parts images into intelligent vector-layered files. The method involves recognizing and removing reference labels from the raster illustrated parts image to produce a reference label scrubbed file. Reference lines are recognized and removed from the reference label scrubbed file to produce a scrubbed file. The scrubbed file includes a reusable base graphic. The scrubbed file is converted to a vector file in which the reusable base graphic is embedded. One or more vector layers are added to the vector file to produce the intelligent vector-layered file. Each vector layer includes vector elements corresponding to one of the recognized reference labels and its one or more reference lines.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional of U.S. patent application Ser. No.10/318,921 filed on Dec. 13, 2002. The disclosure of the aboveapplication is incorporated herein by reference.

COPYRIGHT NOTICE

A portion of the disclosure of this document contains material that issubject to copyright protection. The copyright owner has no objection tothe facsimile reproduction by anyone of the patent disclosure, as itappears in the U.S. Patent and Trademark Office patent files or records,but otherwise the copyright owner reserves all copyright rightswhatsoever.

FIELD OF THE INVENTION

The present invention relates to raster illustrated part images, andmore particularly to apparatus and methods for converting rasterillustrated parts images into intelligent vector-layered files.

BACKGROUND OF THE INVENTION

Illustrated parts drawings identify a hierarchy of details or assembliesand parts in a manner showing how the details and parts fit together.Illustrated parts drawings may show multiple details such as theexemplary illustrated parts drawing shown in FIG. 1 that includes threedetails labeled G, H and I. Typically, the details include references oritems numbers that are indexes into a parts list where additionalinformation about the assemblies and parts is available. A singleillustrated parts drawing can include many details with dozens of itemnumbers.

It is a common practice to use illustrated parts drawings with tasklists. A task list specifies construction or maintenance steps, whereeach step references one or more the parts on the illustrated partsdrawing. For a particular step, a user typically must search the drawingfor the parts referenced in the step to view the part and how it relatesto other parts. However, searching for the part can be time-consumingand prone to errors, especially as the number of parts contained in theillustrated parts drawing increases.

An existing method of improving the usability of electronic illustratedparts images with task lists is to separate the various images of theillustrated parts drawings for each step of the task list and thenidentify only the details and parts referenced in that step. In thismethod, the same base drawing is used repeatedly but with only therelevant, and different, parts being identified each time. This methodimmediately draws the user's attention to the parts or items on thedrawing that are relevant to the current step of the task list. Forexample, FIG. 2 shows an illustrated parts image being used with anexemplary task list. As shown in FIG. 2, the illustrated parts imageidentifies only the parts or items relevant to or mentioned in thecurrent task list step (i.e., “Remove bolts, washers, and nuts”).Although this method has proved successful for its intended purpose, thecost of manually creating and maintaining numerous slightly modifiedversions of the same drawing, however, is prohibitively expensive.

Another method of improving the usability of electronic illustratedparts images is to provide an illustrated parts image with one or moreintelligent objects. Indeed, existing computer software programs andtools allow for the authoring of intelligent illustrated parts imageswith intelligent objects and constructs, such as item numbers andlocators. By way of example only, an illustrated parts image may beprovided with an item number that is disposed at the end of a referenceline (e.g., lead line, leader line, arrow, bulleted line, etc.) and thatis associated with a link or index to database information about theparticular component or part referenced by the item number. Accordingly,a user-click on an item number queries a database and thus allows theuser to access database information associated with the item number. Asanother example, an illustrated parts image may be provided with alocator. As before with item numbers, a locator is also disposed at theend of a reference line. However, a locator is associated with zoomingfunctionality that allows a user to zoom in on a particular portion(e.g., component, part, detail, assembly, etc.) of the illustrated partsdrawing with a user-click on the locator. Accordingly, both item numbersand locators allow a user to access additional information by way of auser-click thereon.

However, there are many existing illustrated parts drawings thatcomprise unintelligent raster images (bitmapped graphics) that do notprovide high-level structures, such as text records or graphicalprimitives. For at least this reason, raster illustrated part imageshave had very limited functionality in electronic information systems.

SUMMARY OF THE INVENTION

Accordingly, the inventors have recognized a need in the art for devicesand methods that improve the usability and functionality of rasterillustrated parts images by converting existing raster illustrated partsimages into intelligent vector-layered files in a highly accurate,efficient, and automated batch process that requires little to no userintervention.

The present invention is directed to a system and method for convertingraster illustrated parts images into intelligent vector-layered files.The method generally involves recognizing and removing reference labelsfrom the raster illustrated parts image to produce a reference labelscrubbed file. Reference lines are recognized and removed from thereference label scrubbed file to produce a scrubbed file, which includesa reusable base graphic. The scrubbed file is converted to a vector filein which the reusable base graphic is embedded as a bitmap. One or morevector layers are added to the vector file to produce an intelligentvector-layered file. Each vector layer includes vector elementscorresponding to one of the recognized reference labels and its one ormore reference lines.

Further areas of applicability of the present invention will becomeapparent from the detailed description provided hereinafter. It shouldbe understood that the detailed description and specific examples, whileindicating at least one preferred embodiment of the invention, areintended for purposes of illustration only and are not intended to limitthe scope of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will become more fully understood from thedetailed description and the accompanying drawings, wherein:

FIG. 1 is an exemplary raster illustrated parts image;

FIG. 2 illustrates an exemplary task list being used in conjunction withan exemplary illustrated parts image;

FIG. 3 is a simplified block diagram of a system in accordance with apreferred embodiment of the present invention;

FIG. 4A is an intelligent vector-layered image with all reference labelsidentified;

FIG. 4B is the image in 4A with only reference labels relevant to aspecific task visible;

FIGS. 5A and 5B form a flowchart of the steps performed during a methodfor converting raster illustrated parts images into intelligentvector-layered files in accordance with a preferred embodiment of thepresent invention;

FIG. 6 is a process flow diagram of various files created and/or usedduring the method shown in FIGS. 5A and 5B;

FIG. 7 is an exemplary raster image fragment in which four binary largeobjects have been identified;

FIGS. 8A, 8B and 8C illustrate the results of the detail separationprocess on the image shown in FIG. 1;

FIG. 9 illustrates the reference labels recognized and removed from theimage shown in FIG. 8A;

FIG. 10 is an illustration of an exemplary pixel run;

FIG. 11A illustrates fifteen (15) pixel runs that can be merged to formthe single pixel run shown in FIG. 11B;

FIG. 11B illustrates the single pixel run formed from the merger of thefifteen (15) pixel runs shown in FIG. 11A;

FIG. 12 shows an exemplary collection of eleven pixel runs forming anoblique line;

FIG. 13 illustrates an exemplary location file containing item number,locator, detail and reference line information;

FIG. 14 is a reusable base graphic generated by the system shown in FIG.3 for the image shown in FIG. 8A;

FIG. 15 is an illustration of an intelligent vector-layered image withall layers activated and that is generated by the system shown in FIG. 3from the image shown in FIG. 8A; and

FIGS. 16A and 16B are intelligent vector-layered image fragments withitems identified with and without item numbers, respectively.

Corresponding reference characters indicate corresponding featuresthroughout the drawings.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The following description of the preferred embodiments is merelyexemplary in nature and is in no way intended to limit the invention,its application, or uses.

Referring to FIG. 3, there is shown a control system 10 in accordancewith a preferred embodiment of the present invention. Generally, thesystem 10 converts raster illustrated parts images 11 into one or moreintelligent vector-layered files 13 in a substantially automated batchprocess. Each intelligent vector-layered file 13 includes a reusablebase graphic and a vector layer for each item number and locator. Eachvector layer also includes the reference line(s) associated with thecorresponding item number or locator.

For ease of identification and description and not for purposes oflimitation, the term “reference label” as used herein shall be construedto include both item numbers and locators. In addition, the term“reference line” as used herein shall be construed to include any of awide range of lines regardless of whether the line has an enddesignator, including but not limited to arrows, lead lines, leaderlines, bulleted lines (i.e., lines with bullets as end designators),among others.

The vector layers are preferably encoded in a file format that iscompatible with existing electronic or drawing management systems toallow authors to link vector layers to related steps of a task list. Atruntime, the vector layers can be activated (i.e., made visible) ordeactivated (i.e., made invisible) so that the items relevant to thecurrent step are identified on the reusable base graphic. See FIGS. 4Aand 4B. In other words, the reusable base graphic and various vectorlayers comprise an intelligent graphic, the display of which variesdepending upon the content or particular step for which the graphics arebeing displayed.

Referring back to FIG. 3, the system 10 includes a suitable processingelement 12 for performing the various operations required by the presentinvention. The processing element 12 is typically comprised of acombination of hardware (e.g., one or more microprocessors, otherprocessing devices) and software that is stored by memory and executedby the hardware. In the illustrated embodiment, the processor 12executes a detail art grouping and separation module 14, a textrecognition and erasure module 16, a line recognition and erasure module18, a graphic normalizer module 20, a vector file conversion module 22,and a vector layer builder and inserter module 24. However, it should beunderstood that the processing element 12 can be comprised of othercombinations of hardware, software, firmware or the like so long as theresulting combination is capable of implementing the various operationsrequired for converting raster illustrated images into one or moreintelligent vector-layered files.

The system 10 also includes memory which may take the form of anysuitable computer readable storage device. For example, the memory maycomprise read only memory (ROM), random access memory (RAM), videomemory (VRAM), hard disk, floppy diskette, compact disc (CD), an opticaldisk, magnetic tape, a combination thereof, etc. The memory may comprisecomputer readable media for storing such items as program code, softwarepackages, programs, algorithms, information, data, files, databases,applications, among other things.

In the embodiment shown in FIG. 3, the system 10 includes the detail artgrouping and separation module 14, the text recognition and erasuremodule 16, the line recognition and erasure module 18, the graphicnormalizer module 20, the vector file conversion module 22, and thevector layer builder and inserter module 24. The plurality of modules 14through 24 may be embodied in computer-readable program code stored inone or more computer-readable storage media operatively associated withthe system 10.

It is to be understood, however, that the computer readable program codedescribed herein can be conventionally programmed using any of a widerange of suitable computer readable programming languages that are nowknown in the art or that may be developed in the future. It is also tobe understood that the computer readable program code described hereincan include one or more functions, routines, subfunctions, andsubroutines, and need not be combined in a single package but mayinstead be embodied in separate components. In addition, the computerreadable program code may be a stand-alone application, or may be aplug-in module for an existing application and/or operating system.Alternatively, the computer readable program code may be integrated intoan application or operating system. In yet another embodiment, thecomputer readable program code may reside at one or more network devices(not shown), such as an administrator terminal, a server, etc.

Although the present invention is described with the various modules 14through 24 having a direct effect on and direct control of the system10, it should be understood that it is the instructions generated by theexecution of the programs 14 through 24 by the processing element 12,and the subsequent implementation of such instructions by the processingelement 12, that have direct effect on and direct control of the system10.

The system 10 further includes data and information specific to the setof raster illustrated parts images being converted. As shown, the system10 includes a plurality of specially built textual character sets 25,26, and 27, one set for the item numbers, one set for the detail labels,and one set for the locator labels. As explained in greater detailbelow, the character sets 25, 26, and 27 are used by the processingelement 12 during detail art grouping and separation and during textrecognition.

A preferred method 30 implemented by the system 10 of the presentinvention is illustrated in simplified flow chart form in FIGS. 5A and5B. FIG. 6 is a process flow diagram showing various files used and/orcreated during the method 30.

As shown in FIG. 5A, step 32 of method 30 comprises inputting one ormore files 132 (FIG. 6) from the illustrated parts document 11 into thesystem 10. By way of example only, the files 132 input at step 32 maycomprise uncompressed TIFF (tagged image file format) files havingvarious resolutions (e.g., 300 dpi (dots per inch) to 700 dpi) andvarious color depths (e.g., color depth of 8 or 256 colors, etc.).

At step 34 (FIG. 5A), the system 10 executes the graphic normalizermodule 20 (FIG. 3) to reformat and standardize each input file 132 (FIG.6) to the same resolution, color depth, and compression. By way ofexample only, the files 134 (FIG. 6) normalized by the system 10 at step34 may be compressed and converted to 300 dpi and 1 bit color(monochrome).

Step 36 (FIG. 5A) comprises a detail art grouping and separation processduring which the system 10 executes the module 14 (FIG. 3) to separatethe details within the normalized files 134 (FIG. 6) into individual ordetail separated files 136. As shown in FIG. 5A, step 38 involves thesystem 10 accessing the character sets 25, 26, and 27 and using opticalcharacter recognition (ocr) to recognize the text (e.g., detail labels,locator labels, item numbers, etc.) within the raster illustrated partsimages contained within the normalized files 134. At step 38, the system10 may, for example, execute optical character recognition (OCR)software, such as Cartouche® OCR computer software from RAF Technology,Inc. of Redmond, Wash.

At step 40, the system 10 stores the recognized text and itscorresponding locations. At step 42, the recognized text is removed orerased from the raster images within the normalized files 134.

At step 44, the system 10 detects and parses the individual detailswithin the raster images of the normalized files 134 by using geometricproximity-based calculations in conjunction with the detail labelsrecognized at step 38. The system 10 uses the detail labels as startingpoints to identify pixels that are connected or grouped together. Thesystem 10 preferably begins searching above the detail labels for thepixels to be grouped for each detail label. Each collection of groupedpixels may include the artwork forming the corresponding detail and itsassociated reference lines. Although the system 10 preferably separatesambiguous images (i.e., images that cannot be separated out with highconfidence), the system 10 also preferably flags the ambiguous images tonotify a user (e.g., illustrator, etc.) of the ambiguity.

At step 46, the system 10 stores each detail found at step 44 in its ownfile 136 (FIG. 6). For example, the three details labeled G, H and I inFIG. 1 would each be written to their own files at step 46 asillustrated in FIGS. 8A, 8B and 8C.

At step 48 (FIG. 5A), the system 10 executes an assignment algorithm toassign and write the text recognized at step 38 to the appropriatedetail file 136. Text assignment is preferably based upon geometricproximity reasoning (i.e., how close a particular text element is to adetail). The unambiguous text is preferably assigned before ambiguoustext (i.e., those that cannot be assigned to a detail with highconfidence). Each text element is preferably assigned to the detail towhich its corresponding reference line is pointing.

Step 50 comprises a reference label recognition and erasure processduring which the system 10 executes the module 16 and optical characterrecognition computer software. The input for the reference labelrecognition and erasure process 50 comprises the detail separated files136. At step 50, the system 10 finds the text corresponding to thereference labels while allowing for at least some deviation in thecharacters.

During the reference label recognition and erasure process 50, thesystem 10 first removes all large binary large objects at step 52 (i.e.,the binary large objects that are too large to be characters) so thatthe same may be ignored during the reference label recognition anderasure process 50. Ignoring the large binary large objectssubstantially improves the system's 10 processing speed and accuracyduring the reference label recognition and erasure process 50. As usedherein, a “binary large object” (BLOB) is a grouping of all visiblepixels that are connected, either horizontally, vertically ordiagonally, to one or more other visible pixels in the grouping. Avisible pixel is a pixel whose color is different than that of thebackground color of the image. In FIG. 7, there is shown an illustrationof an exemplary raster image fragment in which four binary large objectsor blobs have been identified.

Referring back to FIG. 5A, step 54 comprises character recognitionduring which the system 10 runs a character recognition engine on theremaining “small” blobs (i.e., those binary large objects or blobs thatare not too large to be characters). During step 54, the system 10accesses the data within the character sets 25, 26, and 27 to locate thecharacters within the detail separated files 136.

At step 56, the system 10 uses the output from the character recognitionstep 54 to find reference labels, classifying them as item numbers,locator labels or detail labels. FIG. 9 shows the reference labels thatwere found in FIG. 8A by the system 10.

At step 58 (FIG. 5A), each recognized reference label and its respectiveplacement or position on the image is captured or stored in anintermediate version of the raster file. The pixels representing eachreference label are then erased or scrubbed from the images at step 60to produce reference label scrubbed raster files 160 (FIG. 6).

Referring now to FIG. 5B, step 62 comprises a line recognition anderasure process during which the system 10 executes module 18 toidentify, store, and erase the reference lines associated with thereference labels. The input for the line recognition and erasure process62 comprises the reference label scrubbed raster files 160 (FIG. 6).

At step 64 (FIG. 5B), the system 10 builds an ordered list of pixel runsfrom a reference label scrubbed raster file 160. As used herein, a“pixel run” is a grouping of pixels that are adjacent horizontally andshare the same y-coordinate, as shown in FIG. 10. The initial runs builtat step 64 each have a height of one (1) pixel but may have varyinglengths or widths depending on how many adjacent pixels are found. Atypical raster image may include tens of thousands of pixel runs.

At step 66 (FIG. 5B), the pixel runs having identical x-coordinates andadjacent y-coordinates are merged. When a run is merged with another runit is removed from the list of runs. The remaining run is modified sothat it is now “thicker” or “taller” than it was before the merge. Forexample, FIG. 11A shows fifteen (15) pixel runs, each having a width orlength of three (3) pixels and height of one (1) pixel, that can bemerged to form the single pixel run of width three (3) pixels and heightof fifteen (15) pixels shown in FIG. 11B. Accordingly, horizontal linesare merged runs whose widths exceed their heights while meeting aminimum length requirement, whereas vertical lines are merged runs whoseheights exceed their widths while meeting a minimum length requirement.Oblique lines are made of pixel runs that are “staircased”, as shown inFIG. 12.

At step 68 (FIG. 5B), the system 10 searches for starting positions forreference lines by searching for pixels in the immediate proximity towhere reference labels were recognized at step 50. That is, a line startis located by finding a pixel run in the immediate proximity to where areference label was located. Once found, the pixel run is used as astarting point or seed by the system 10 to locate adjacent pixel runsthat also proceed in the substantially same direction and along asubstantially constant slope as the starting pixel run. When the system10 cannot locate anymore of such adjacent pixel runs, a determination ismade as to whether the collection of pixel runs, now forming a line, issufficiently long enough for consideration as a reference line. If not,the system 10 selects another pixel run for use as starting point orseed and builds collection of pixel runs therefrom in the manner justdescribed.

It should be noted that the resolution for the raster illustrated partsimages being converted may vary depending on the particular applicationin which the present invention is being used. Accordingly, thedetermination of when a collection of pixel runs is long enough forconsideration as a reference line will also vary depending on theparticular application in which the present invention is being used. Byway of example only, a reference line might be required to be at leastfive to ten percent (5-10%) coverage of the artwork.

In the illustrated embodiment, the system 10 tests at step 70 for thepresence of an arrowhead at the end of each potential reference line(i.e., the pixel run collections that are sufficiently long enough to beconsidered a reference line). The system 10 works backward from a linestopping point and looks for pixel runs forming an arrowhead shape. Ifan arrowhead is found, the object (i.e., the line and arrowhead) isconsidered a valid reference line. After a valid reference line islocated for a reference label, the system 10 may continue searching forother reference lines for the reference label because a single referencelabel may have more than one reference line associated therewith, asshown for the item number 435 in the detail labeled G in FIG. 1.

If no arrowhead is found for a line at step 70, the system 10 does notconsider the line to be a reference line. The system 10 does, however,continue testing other lines for arrowheads. It should be noted,however, that the system 10 can also be configured to search for othertypes of lines, such as lines with bullets instead of arrows, lead lines(i.e., lines without end designators), etc.

At step 72, the system 10 writes one or more location files 172 (FIG. 6)that contain data and information about the text strings for referencelabels as well as their respective image locations. The location files172 also contain data and information pertaining to the start and endlocations of each reference line. In FIG. 13, there is shown anexemplary location file wherein “IN” refers to Item Number, “LO” refersto Locator, “DL” refers to Detail and “LL” refers to Leader Line.

At step 73 (FIG. 5B), the system 10 creates the scrubbed files 173 (FIG.6) containing the reusable base graphic(s) (e.g., FIG. 14) by erasingthe pixels forming the reference lines, and accompanying arrowheads fromthe reference label scrubbed files 160. However, the system 10 looks forpixels adjacent to the reference line in order to avoid erasing pixelsthat are also part of or overlapping other objects on the image.

At step 74 (FIG. 5B), the system 10 executes the module 20 (FIG. 3) toreformat and standardize the scrubbed files 173 (FIG. 6). At step 76(FIG. 5B), the system 10 executes the module 22 (FIG. 3) to convert thenormalized scrubbed files 174 (FIG. 6) into vector files 176 thatinclude the reusable base graphics as embedded bitmaps.

By way of example only, the system 10 may encode the vector files 176 ina file format called Computer Graphic Metafile (CGM), a widely-usedtechnical illustration format. Alternatively, however, other languagesand file formats may be used by the system 10 to encode the vector files176 including, but not limited to, DWG format, document exchange format(DXF), initial graphics exchange specification (IGES) format, amongothers.

At step 78 (FIG. 5B), the system 10 executes the module 24 (FIG. 3) tocreate the intelligent vector-layered files 178 (FIG. 6). That is, thesystem 10 reintroduces into the vector files 176 the reference labelsand their associated reference lines as vector elements with eachreference label being within a separate vector layer. As used herein, a“vector layer” shall be construed to include one or more vector elementsthat can be dynamically rendered or hidden at run-time under programcontrol. As evident by comparing FIGS. 8A and 15, the intelligentvector-layered image (FIG. 15) appears substantially identical to theoriginal raster image shown in FIG. 8A when all layers of theintelligent vector-layered image are turned on.

During step 78 (FIG. 5B), the system 10 accesses the location files 172(FIG. 6) and uses the information contained therein to create a separatevector layer for each reference label and its corresponding referenceline(s). Accordingly, in the illustrated embodiment, each vector layercontains the lines emanating from the reference label, a polygon for thearrowhead at the end of each line, and a circle (for item numbers) orrectangle (for locator and detail labels) at the location of thereference label. Appropriate vector elements may be used to encapsulatethe circle or rectangle so that it becomes a hotspot upon which a usercan click to access the corresponding part information or detail. Thetext strings for the reference labels in the corresponding vector layersare located in substantially identical positions as they were in theoriginal raster illustrated parts image 11.

Upon completion of step 78, the intelligent vector-layered files 178 maybe saved on a suitable computer readable medium at step 80 (FIG. 5B).Alternatively, or additionally, the intelligent vector-layered files 178may be output at step 82, for example, to a graphical display.

The reference labels and their reference lines may also be encoded inextensible markup language (XML). In addition, the intelligentvector-layered files 178 preferably comprise CGM Version 4 files, whichallow for the control of vector layers by existing graphic displaysoftware and allow vector layers to be made visible individually or as agroup. Alternatively, however, other languages and file formats may beused for the intelligent vector-layered files.

In any event, the intelligent vector-layered files 178 allow documentauthors to control what layers are visible and when. Thus, one rasterillustrated parts image with tens or hundreds of items may be reusedrepeatedly while displaying only the items applicable to a particularstep in the task list, as shown by comparing FIG. 4A (identifying allreference labels) and FIG. 4B (identifying reference labels relevant toa particular step).

Referring now to FIG. 16A, item number text may be included as an aidwhen document authors are working with the intelligent vector-layeredimages. Document authors might need to know what each item number refersto because item number text is typically an index into a database partstable. However, it is usually not necessary for the item number text tobe displayed (FIG. 16B) for users viewing the illustrated parts imageswith an electronic information system because the electronic informationsystem can perform the table lookup and return the resultsautomatically, thus eliminating the need for the users to know the itemnumber text or do the cross-referencing manually.

The system 10 preferably comprises a batch conversion processor and thusdoes not require significant human intervention or manual re-authoringof the raster images. Accordingly, the present invention provides a morepractical and cost-effective solution to the task of converting rasterillustrated parts images to intelligent vector-layered files than thesolutions presently recognized in the art, such as manually re-authoringor converting illustrated parts drawings with commercially availabletools.

By accurately and quickly converting caster illustrated parts images tointelligent vector-layered files, the present invention dramaticallyimproves the usability of the data within illustrated parts drawings.For example, the intelligent vector-layered files are suitable forintegration with other intelligent graphics capabilities, advanced andefficient user interaction, among other functional capabilities.

In addition, the present invention is highly accurate in recognizingreference labels and reference lines from raster images. Indeed, thepresent invention provides a high quality but inexpensive approach forconverting paper and raster illustrated parts drawings into intelligentvector-layered drawings. The present invention also eliminates, or atleast reduces, the need for paper-based deliveries of illustrated partsdrawings in that paper-based illustrated parts drawings can be scannedand then converted by the present invention to intelligentvector-layered drawings.

It is anticipated that the invention will be applicable to any of a widerange of raster graphics. Accordingly, the specific references to rasterillustrated parts images herein should not be construed as limiting thescope of the present invention, as the invention could be applied toconvert other raster images to intelligent vector-layered images,including but not limited to assembly instructions for consumerproducts, assembly instructions in the automotive industry, amongothers.

The description of the invention is merely exemplary in nature and,thus, variations that do not depart from the substance of the inventionare intended to be within the scope of the invention. Such variationsare not to be regarded as a departure from the spirit and scope of theinvention.

1. A method for separating details of a raster illustrated parts image,comprising: recognizing text within the raster illustrated parts image;removing the recognized text from the raster illustrated parts image;analyzing the raster illustrated parts image to identify and grouptogether pixels that comprise artwork forming a detail of the rasterillustrated parts image, to enable details of the raster illustratedparts image to be parsed as part of separate detail files; assigningeach detail of the raster illustrated parts image to its own detailfile; assigning each text element of the recognized text to a detailfile based on a correspondence between the text element and a referenceline, if any, pointing to a raster illustrated parts image detailassigned to the detail file; removing reference labels and referencelines from the detail files to obtain scrubbed files each including areusable base graphic; and converting each scrubbed file to a vectorlayered file in which each reference label is in a separate vectorlayer; the vector layers controllable to selectively display one or moreof the reference labels with the reusable base graphic; the methodperformed by one or more processors using memory configured with the oneor more processors.
 2. The method of claim 1, wherein analyzing theraster illustrated parts image comprises using geometric proximity-basedcalculations together with recognized detail labels in said rasterillustrated parts image.
 3. The method of claim 1, wherein for eachdetail, the corresponding reusable base graphic is embedded in thecorresponding vector file.
 4. The method of claim 1, further comprisingmaking a reference label location indicator in a vector layerselectively activatable by a user to obtain part informationcorresponding to the reference label.
 5. The method of claim 1, whereinthe operations of recognizing and removing the recognized text compriseusing optical character recognition and at least one predefinedcharacter set associated with the raster illustrated parts image.
 6. Themethod of claim 5, wherein using at least one predefined character setcomprises using a character set of at least one of: detail labels;locator labels; and item numbers.
 7. The method of claim 6, whereinassigning the recognized text comprises using geometric proximityreasoning, and a detail label of said raster illustrated parts image asa starting point, to assign the recognized text to a corresponding oneof said detail files.
 8. The method of claim 7, wherein assigning therecognized text comprises assigning less ambiguous recognized textbefore assigning more ambiguous recognized text.
 9. The method of claim1, further comprising linking the vector layers with steps in a tasklist.
 10. A method for separating details of a raster illustrated partsimage, comprising: a) recognizing and removing text from the rasterillustrated parts image by using optical character recognition and atleast one character set associated with the raster illustrated partsimage; b) detecting and parsing the details of the raster illustratedparts image using geometric proximity-based calculations and detaillabels recognized in operation a); c) storing each detected and parseddetail in a corresponding detail file; d) assigning each text element ofthe recognized text to a corresponding detail file using geometricproximity reasoning; e) removing reference labels from the detail filesto obtain reference-label-scrubbed files; f) using an ordered list ofpixel runs, removing reference lines from the reference-label-scrubbedfiles to obtain scrubbed files each including a reusable base graphic;and g) converting each scrubbed file to a vector layered file in whicheach reference label and corresponding reference line is in a separatevector layer; the vector layers controllable to selectively display oneor more of the reference labels with the reusable base graphic; whereinthe operations a), b), c), d), e), f) and g) are performed by one ormore processors using memory configured with the one or more processors.11. The method of claim 10, further comprising making a reference labellocation indicator in a vector layer selectively activatable by a userto obtain part information corresponding to the reference label.
 12. Themethod of claim 10, wherein the operation of using one character set inoperation a) comprises using one set of item numbers.
 13. The method ofclaim 10, wherein the operation of using one character set in operationa) comprises using one set of detail labels.
 14. The method of claim 10,wherein the operation of using one character set in operation a)comprises using one set of locator labels.
 15. The method of claim 10,wherein the operation of recognizing and detecting text in operation a)comprises storing each text element of the recognized text and itscorresponding location.
 16. The method of claim 10, further comprisinglinking the vector layers with one or more steps in a task list.
 17. Asystem for identifying and separating out details of a rasterillustrated parts image, comprising: one or more processors and memoryconfigured with the one or more processors; the memory havinginstructions stored thereon and executable by the one or more processorsto: recognize text within the raster illustrated parts image, and toseparate details within the raster illustrated parts image into separatedetail files; assign each text element of the recognized text to adetail file based on a correspondence between the text element and areference line, if any, pointing to a raster illustrated parts imagedetail assigned to the detail file; remove reference labels andreference lines from the detail files to obtain scrubbed files eachincluding a reusable base graphic; convert each scrubbed file to avector file in which the reusable base graphic is embedded; and add oneor more vector layers to each vector file each vector layer controllableto selectively display a corresponding reference label and referenceline with the reusable base graphic.
 18. The system of claim 17, whereinsaid one or more processors and memory are configured to analyze theraster illustrated parts image to identify and group together pixelsthat comprise artwork forming a detail of the raster illustrated partsimage, to enable details of the raster illustrated parts image to beparsed as part of separately formed detail files.
 19. The system ofclaim 17, wherein the one or more processors and memory are configuredto use optical character recognition to identify text within said rasterillustrated parts image.
 20. The system of claim 19, wherein the opticalcharacter recognition is used to identify at least one of the following:detail labels, locator labels, and item numbers present within saidraster illustrated parts image.